The Michigan Engineer News Center

Siqian Shen receives funding from Ford to design integrated ridesharing and goods delivery system

U-M IOE associate professor, Siqian Shen, has received research funding from Ford to explore how mathematical optimization and operations research approaches can improve services that integrate ridesharing with goods delivery.| Short Read

Siqian Shen, associate professor, U-M Industrial and Operations Engineering (IOE), has received research funding from Ford Motor Company to explore how mathematical optimization and operations research approaches can be used to design and improve services that integrate ridesharing with goods delivery.

Shared mobility systems like ridesharing have become widely used to deliver goods and services to customers whose orders usually arrive dynamically in real time — meaning that a business receives orders from customers once operations are already underway rather than ahead of time. As a result, the design and operations of such systems need to be highly flexible, while guaranteeing cost-effective solutions (including resource allocation, consolidation, and vehicle dispatch) and a high quality-of-service.

“The main challenge is how to combine our prior work on static system layout and operations design, with stochastic routing and scheduling decisions, to allow real-time vehicle dispatch and demand response,” said Shen.

“The main challenge is how to combine our prior work on static system layout and operations design, with stochastic routing and scheduling decisions, to allow real-time vehicle dispatch and demand response.” Siqian Shen, Associate Professor, U-M Industrial & Operations Engineering

The results of the study will be applied to Ford Non-Emergency Medical Transportation (NEMT) to utilize the idle time of vehicles and enable the delivery of medicine or standard medical care such as flu shots to individual’s homes.

“We will push the modeling and computational frontiers of stochastic dynamic programming techniques to seek easy-to-implement policies and quick-but-good-quality solutions,” said Shen. “These solutions cannot be obtained by the traditional dynamic programming approach.”

Shen joined the U-M IOE in 2011. Her research area is integer programming, stochastic programming, and network optimization. The models she considers usually feature stochastic parameters and discrete decision variables. Applications of her research include risk analysis and optimization of energy, healthcare, cloud-computing, and transportation systems.

Researchers
  • Siqian Shen

    Siqian Shen

    Associate Professor of Industrial and Operations Engineering

The electrons absorb laser light and set up “momentum combs” (the hills) spanning the energy valleys within the material (the red line). When the electrons have an energy allowed by the quantum mechanical structure of the material—and also touch the edge of the valley—they emit light. This is why some teeth of the combs are bright and some are dark. By measuring the emitted light and precisely locating its source, the research mapped out the energy valleys in a 2D crystal of tungsten diselenide. Credit: Markus Borsch, Quantum Science Theory Lab, University of Michigan.

Mapping quantum structures with light to unlock their capabilities

Rather than installing new “2D” semiconductors in devices to see what they can do, this new method puts them through their paces with lasers and light detectors. | Medium Read